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학술대회 AI-based Network Security Enhancement for 5G Industrial IoT Environments
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이종훈, 김현진, 박철희, 김영수, 박종근
International Conference on Information and Communication Technology Convergence (ICTC) 2022, pp.971-975
22HR2400, 5G+ 서비스 안정성 보장을 위한 엣지 시큐리티 기술 개발, 박종근
The recent 5G networks aim to provide higher speed, lower latency, and greater capacity; therefore, compared to the previous mobile networks, more advanced and intelligent network security is essential for 5G networks. To detect unknown and evolving 5G network intrusions, this paper presents an artificial intelligence (AI)-based network threat detection system to perform data labeling, data filtering, data preprocessing, and data learning for 5G network flow and security event data. The performance evaluations are first conducted on two well-known datasets-NSL-KDD and CICIDS 2017; then, the practical testing of proposed system is performed in 5G industrial IoT environments. To demonstrate detection against network threats in real 5G environments, this study utilizes the 5G model factory, which is downscaled to a real smart factory that comprises a number of 5G industrial IoT-based devices.
KSP 제안 키워드
5G Network, Data Labeling, Data Learning, Data Preprocessing, Intrusion detection system(IDS), IoT environment, IoT-based, Mobile networks, NSL-KDD, Network Threat, Network flow